HEALTH PERCEPTIONS, USE OF HEALTH SERVICES AND EMPLOYMENT STATUS OF WOMEN.
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PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Degree ProgramGraduate College
Degree GrantorUniversity of Arizona
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Modeling the cost-effectiveness of a regional poison control center using decision analysisDraugalis, JoLaine R.; Harrison, Donald Lee, 1956- (The University of Arizona., 1996)Using decision analysis techniques, the cost-effectiveness of two alternatives for treating human poison exposures were modeled. The alternatives were the treatment of poisonings with the services of a regional poison control center versus without access to any poison control center. The relative cost-effectiveness was modeled based on two outcomes (morbidity and mortality) for each of four typical poison exposures: acetaminophen overdose, tricyclic antidepressant overdose, cleaning substance exposure in children, and cough/cold preparation overdose in children. Additionally, analyses were conducted to test the sensitivity of the cost-effectiveness ratio to outcome probability, average inpatient and emergency room charges, and proportion of poison exposures managed on site by the regional poison control center. This research was conducted from society's point of view.
An expanding framework for rural patients who travel for health careLamb, Gerri; Sweeney Fee, Sharon K. (The University of Arizona., 2004)This exploratory study utilized Donabedian's Quality model to develop a framework to study patients who must migrate for health care. One year of the Arizona Department of Health Services Discharge Database was used to analyze patient characteristics that influenced discharge travel and the impact of distance on risk adjusted patient outcomes. Geographic Interface software was used to identify rural patients, defined as those with zip codes farther than thirty miles from hospitals. Zip Code analysis was used to create distance variables between 31 and over 300 miles. The key findings for patients who traveled greater distances included larger hospitals, emergency admission type, private insurance, critical care services, and Neuro/Ortho/Trauma diagnosis group. Patients which traveled shorter distances included smaller hospitals, referral or transfer admit source, AHCCCS insurance (or Medicaid) and Women's Health diagnosis group. Outcomes were risk adjusted using age and distance was significant for both number of procedures and length of stay. Patients who traveled farther received fewer procedures and had a greater length of stay. A preliminary cost analysis of the length of stay outliers identified approximately four million dollars in potentially non-reimbursable charges.
Development of the Diabetes Resource Consumption Index and profiling quality of diabetes care in the Veterans Health AdministrationMalone, Daniel C.; Joish, Vijay (The University of Arizona., 2003)The purpose of this study was to develop and validate a risk-adjustment index for one year healthcare resource use specific to diabetic patients, based on severity of illness measures; and to profile quality of diabetes care between outpatient clinics. The data for this study was collected from four outpatient clinics within the Southern Arizona Veterans Affairs Healthcare System, Tucson, AZ. The DRCI was developed using a sample size of 367 diabetic subjects that had complete information on diabetes-specific variables. Individual DRCI weights, based on the magnitude of one year healthcare resource use and socio-demographic characteristics, ranged from -471.5 to 3,081.2 for total healthcare costs, from -304.3 to 1,582.1 for outpatient costs, and -0.19 to 0.93 for risk of hospitalization. The DRCI was better than or equivalent to the Chronic Disease Score in predicting health care costs. Diabetics in the second cohort were predominantly elderly (mean = 66yrs ± 11.1), married (61%), white (73%), males (96%), had a high BMI (31 ± 6.3 kg/m²), and mean comorbidity score of 4.2 ± 1.8 conditions. Screening for HbA1c and microalbuminuria was frequently performed in all clinics. Overall, 61% and 36% of study patients did not have evidence of foot or eye examinations during the entire study period, respectively. Approximately, 27% (n = 408), 41% (n = 643), and 26% (n = 515) of the study patients had poor glycemic, renal function, and lipid control, respectively. Significant differences (p < .05) in HbA1c and creatinine clearance rates between the clinics were observed after adjusting for patient case-mix. However, differences between the clinics in cardiovascular outcome were not observed after adjusting for patient case-mix. This study demonstrated an association between diabetes severity with healthcare resource and costs. The DRCI, using laboratory data, is a diabetes-specific severity measure for prediction of one year healthcare resource use. Future studies are needed to validate this index in other settings. Finally, the results from this study emphasize the need to adjust for case-mix variable when comparing quality of diabetic care outcomes between outpatient clinics.